{
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   "source": [
    "HW2: Logistic 回归&SVM\n",
    "1、 任务描述\n",
    "请在 Pima Indians Diabetes Data Set（皮马印第安人糖尿病数据集）进行分类器练习。\n",
    "\n",
    "\n",
    "需要提交代码文件，并给出必要的结果解释。\n",
    "1)  训练数据和测试数据分割（随机选择 20%的数据作为测试集）；（10 分）\n",
    "2)  适当的特征工程（及数据探索）;（10 分）\n",
    "3)  Logistic 回归，并选择最佳的正则函数（L1/L2）及正则参数；（30 分）\n",
    "4)  线性 SVM，并选择最佳正则参数，比较与 Logistic 回归的性能，简单说明原因。\n",
    "（20 分）\n",
    "5)  RBF 核的 SVM，并选择最佳的超参数（正则参数、RBF 核函数宽度）；（30 分）\n",
    "2、 数据说明：\n",
    "原始数据集地址： https://archive.ics.uci.edu/ml/datasets/Pima+Indians+Diabetes \n",
    "数据集只有一个文件（diabetes.csv）：Pima Indians Diabetes Dataset 包括根据医疗\n",
    "记录的比马印第安人 5 年内糖尿病的发病情况，这是一个两类分类问题。每个类的\n",
    "样本数目数量不均等。一共有 768 个样本，每个样本有 8 个输入变量和 1 个输出\n",
    "变量。缺失值通常用零值编码。\n",
    "1)  字段说明\n",
    "Pregnancies： 怀孕次数\n",
    "Glucose： 口服葡萄糖耐受试验中，2 小时的血浆葡萄糖浓度。\n",
    "BloodPressure： 舒张压（mm Hg）\n",
    "SkinThickness： 三头肌皮肤褶层厚度（mm）\n",
    "Insulin：2 小时血清胰岛素含量（μU/ ml）\n",
    "BMI： 体重指数（体重，kg /（身高，m）^ 2）\n",
    "2)  DiabetesPedigreeFunction： 糖尿病家族史\n",
    "3)  Age： 年龄（岁）\n",
    "Outcome： 输出变了/类别标签（0 或 1，出现糖尿病为 1, 否则为 0）"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 156,
   "metadata": {},
   "outputs": [],
   "source": [
    "import numpy as np#线性代数\n",
    "import pandas as pd#SOL数据处理\n",
    "\n",
    "import matplotlib.pyplot as plt #画图\n",
    "from matplotlib import pyplot\n",
    "import seaborn as sns\n",
    "\n",
    "#from sklearn.metrics import r2_score \n",
    "from sklearn.metrics import accuracy_score\n",
    "from sklearn.metrics import classification_report"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 157,
   "metadata": {},
   "outputs": [
    {
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       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
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       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>6</td>\n",
       "      <td>148</td>\n",
       "      <td>72</td>\n",
       "      <td>35</td>\n",
       "      <td>0</td>\n",
       "      <td>33.6</td>\n",
       "      <td>0.627</td>\n",
       "      <td>50</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>1</td>\n",
       "      <td>85</td>\n",
       "      <td>66</td>\n",
       "      <td>29</td>\n",
       "      <td>0</td>\n",
       "      <td>26.6</td>\n",
       "      <td>0.351</td>\n",
       "      <td>31</td>\n",
       "      <td>0</td>\n",
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       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>8</td>\n",
       "      <td>183</td>\n",
       "      <td>64</td>\n",
       "      <td>0</td>\n",
       "      <td>0</td>\n",
       "      <td>23.3</td>\n",
       "      <td>0.672</td>\n",
       "      <td>32</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>1</td>\n",
       "      <td>89</td>\n",
       "      <td>66</td>\n",
       "      <td>23</td>\n",
       "      <td>94</td>\n",
       "      <td>28.1</td>\n",
       "      <td>0.167</td>\n",
       "      <td>21</td>\n",
       "      <td>0</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>0</td>\n",
       "      <td>137</td>\n",
       "      <td>40</td>\n",
       "      <td>35</td>\n",
       "      <td>168</td>\n",
       "      <td>43.1</td>\n",
       "      <td>2.288</td>\n",
       "      <td>33</td>\n",
       "      <td>1</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "   Pregnancies  Glucose  BloodPressure  SkinThickness  Insulin   BMI  \\\n",
       "0            6      148             72             35        0  33.6   \n",
       "1            1       85             66             29        0  26.6   \n",
       "2            8      183             64              0        0  23.3   \n",
       "3            1       89             66             23       94  28.1   \n",
       "4            0      137             40             35      168  43.1   \n",
       "\n",
       "   DiabetesPedigreeFunction  Age  Outcome  \n",
       "0                     0.627   50        1  \n",
       "1                     0.351   31        0  \n",
       "2                     0.672   32        1  \n",
       "3                     0.167   21        0  \n",
       "4                     2.288   33        1  "
      ]
     },
     "execution_count": 157,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#数据探索\n",
    "DiabetesData = pd.read_csv(\"diabetes.csv\")#读取数据\n",
    "DiabetesData.head()\n",
    "#了解到1.数据的各特征取值区间不同，需进行标准化\n",
    "#      2.观察前5行，特征有0值\n",
    "#      3.观察无日期型，文本型特征，至于类别性特征初步判断只有输出特征，暂定其他均为数值型特征"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 158,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<class 'pandas.core.frame.DataFrame'>\n",
      "RangeIndex: 768 entries, 0 to 767\n",
      "Data columns (total 9 columns):\n",
      "Pregnancies                 768 non-null int64\n",
      "Glucose                     768 non-null int64\n",
      "BloodPressure               768 non-null int64\n",
      "SkinThickness               768 non-null int64\n",
      "Insulin                     768 non-null int64\n",
      "BMI                         768 non-null float64\n",
      "DiabetesPedigreeFunction    768 non-null float64\n",
      "Age                         768 non-null int64\n",
      "Outcome                     768 non-null int64\n",
      "dtypes: float64(2), int64(7)\n",
      "memory usage: 54.1 KB\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "Pregnancies                 0\n",
       "Glucose                     0\n",
       "BloodPressure               0\n",
       "SkinThickness               0\n",
       "Insulin                     0\n",
       "BMI                         0\n",
       "DiabetesPedigreeFunction    0\n",
       "Age                         0\n",
       "Outcome                     0\n",
       "dtype: int64"
      ]
     },
     "execution_count": 158,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DiabetesData.info()\n",
    "DiabetesData.isnull().sum()\n",
    "#由信息可知：无缺失值（或者原数据集已将缺失值零值编码转换成现数据集（现学习器数据集））"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 159,
   "metadata": {},
   "outputs": [
    {
     "data": {
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>Pregnancies</th>\n",
       "      <th>Glucose</th>\n",
       "      <th>BloodPressure</th>\n",
       "      <th>SkinThickness</th>\n",
       "      <th>Insulin</th>\n",
       "      <th>BMI</th>\n",
       "      <th>DiabetesPedigreeFunction</th>\n",
       "      <th>Age</th>\n",
       "      <th>Outcome</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>count</th>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "      <td>768.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>mean</th>\n",
       "      <td>3.845052</td>\n",
       "      <td>120.894531</td>\n",
       "      <td>69.105469</td>\n",
       "      <td>20.536458</td>\n",
       "      <td>79.799479</td>\n",
       "      <td>31.992578</td>\n",
       "      <td>0.471876</td>\n",
       "      <td>33.240885</td>\n",
       "      <td>0.348958</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>std</th>\n",
       "      <td>3.369578</td>\n",
       "      <td>31.972618</td>\n",
       "      <td>19.355807</td>\n",
       "      <td>15.952218</td>\n",
       "      <td>115.244002</td>\n",
       "      <td>7.884160</td>\n",
       "      <td>0.331329</td>\n",
       "      <td>11.760232</td>\n",
       "      <td>0.476951</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>min</th>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.078000</td>\n",
       "      <td>21.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>25%</th>\n",
       "      <td>1.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>62.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>0.000000</td>\n",
       "      <td>27.300000</td>\n",
       "      <td>0.243750</td>\n",
       "      <td>24.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>50%</th>\n",
       "      <td>3.000000</td>\n",
       "      <td>117.000000</td>\n",
       "      <td>72.000000</td>\n",
       "      <td>23.000000</td>\n",
       "      <td>30.500000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>0.372500</td>\n",
       "      <td>29.000000</td>\n",
       "      <td>0.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>75%</th>\n",
       "      <td>6.000000</td>\n",
       "      <td>140.250000</td>\n",
       "      <td>80.000000</td>\n",
       "      <td>32.000000</td>\n",
       "      <td>127.250000</td>\n",
       "      <td>36.600000</td>\n",
       "      <td>0.626250</td>\n",
       "      <td>41.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>max</th>\n",
       "      <td>17.000000</td>\n",
       "      <td>199.000000</td>\n",
       "      <td>122.000000</td>\n",
       "      <td>99.000000</td>\n",
       "      <td>846.000000</td>\n",
       "      <td>67.100000</td>\n",
       "      <td>2.420000</td>\n",
       "      <td>81.000000</td>\n",
       "      <td>1.000000</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "       Pregnancies     Glucose  BloodPressure  SkinThickness     Insulin  \\\n",
       "count   768.000000  768.000000     768.000000     768.000000  768.000000   \n",
       "mean      3.845052  120.894531      69.105469      20.536458   79.799479   \n",
       "std       3.369578   31.972618      19.355807      15.952218  115.244002   \n",
       "min       0.000000    0.000000       0.000000       0.000000    0.000000   \n",
       "25%       1.000000   99.000000      62.000000       0.000000    0.000000   \n",
       "50%       3.000000  117.000000      72.000000      23.000000   30.500000   \n",
       "75%       6.000000  140.250000      80.000000      32.000000  127.250000   \n",
       "max      17.000000  199.000000     122.000000      99.000000  846.000000   \n",
       "\n",
       "              BMI  DiabetesPedigreeFunction         Age     Outcome  \n",
       "count  768.000000                768.000000  768.000000  768.000000  \n",
       "mean    31.992578                  0.471876   33.240885    0.348958  \n",
       "std      7.884160                  0.331329   11.760232    0.476951  \n",
       "min      0.000000                  0.078000   21.000000    0.000000  \n",
       "25%     27.300000                  0.243750   24.000000    0.000000  \n",
       "50%     32.000000                  0.372500   29.000000    0.000000  \n",
       "75%     36.600000                  0.626250   41.000000    1.000000  \n",
       "max     67.100000                  2.420000   81.000000    1.000000  "
      ]
     },
     "execution_count": 159,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DiabetesData.describe()\n",
    "#查看各属性统计特性，\n",
    "#观察到：\n",
    "#1.输入特征的标准差的值没有在百分位级别的，即不可视为常量\n",
    "#2.观察各均值，四分之三位距，最大值，初步拟猜测有无离群点可能"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 160,
   "metadata": {},
   "outputs": [
    {
     "data": {
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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d69b8d7390>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d69b88a198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "cols = [\"Pregnancies\",\"Glucose\",\"BloodPressure\",\"SkinThickness\",\"Insulin\",\"BMI\",\"DiabetesPedigreeFunction\",\"Age\"]\n",
    "fig = plt.figure(figsize = (10,40))\n",
    "for sp in range(0,8):\n",
    "    ax = fig.add_subplot(8,1,sp + 1)\n",
    "    #ax.plot(range(DiabetesData.shape[0]),DiabetesData[cols[sp]].values,c = \"red\")\n",
    "    sns.distplot(DiabetesData[cols[sp]].values, bins=30, kde=True)\n",
    "    #plt.scatter(range(DiabetesData.shape[0]),DiabetesData[cols[sp]].values,color='blue')\n",
    "    for key,spine in ax.spines.items():\n",
    "        spine.set_visible(False)\n",
    "    ax.set_title(cols[sp])\n",
    "plt.show()\n",
    "cols = [\"Pregnancies\",\"Glucose\",\"BloodPressure\",\"SkinThickness\",\"Insulin\",\"BMI\",\"DiabetesPedigreeFunction\",\"Age\"]\n",
    "fig = plt.figure(figsize = (10,40))\n",
    "for sp in range(0,8):\n",
    "    ax = fig.add_subplot(8,1,sp + 1)\n",
    "    #ax.plot(range(DiabetesData.shape[0]),DiabetesData[cols[sp]].values,c = \"red\")\n",
    "    #sns.distplot(DiabetesData[cols[sp]].values, bins=30, kde=True)\n",
    "    ax.scatter(range(DiabetesData.shape[0]),DiabetesData[cols[sp]].values,color='blue')\n",
    "    for key,spine in ax.spines.items():\n",
    "        spine.set_visible(False)\n",
    "    ax.set_title(cols[sp])\n",
    "plt.show()\n",
    "#经观察，Glucose"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 161,
   "metadata": {},
   "outputs": [],
   "source": [
    "#删除相关离群点样本\n",
    "DiabetesData = DiabetesData[DiabetesData.Pregnancies<15.0]\n",
    "DiabetesData = DiabetesData[DiabetesData.Glucose>25]\n",
    "DiabetesData = DiabetesData[DiabetesData.BloodPressure>20]\n",
    "DiabetesData = DiabetesData[DiabetesData.SkinThickness<80]\n",
    "DiabetesData = DiabetesData[DiabetesData.Insulin<600]\n",
    "DiabetesData =DiabetesData[DiabetesData.BMI<60]\n",
    "DiabetesData[DiabetesData.BMI>10]\n",
    "DiabetesData = DiabetesData[DiabetesData.DiabetesPedigreeFunction<2.0]\n",
    "DiabetesData = DiabetesData[DiabetesData.Age<70]\n",
    "#不想考虑两两之间相关性，因为维数不多，降维可能会造成有效信息的缺失"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 162,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(715, 9)"
      ]
     },
     "execution_count": 162,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "DiabetesData.shape"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 163,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "Text(0,0.5,'val')"
      ]
     },
     "execution_count": 163,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": "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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d69b8e29b0>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "sns.countplot(DiabetesData.Outcome)\n",
    "plt.xlabel(\"Outcome\")\n",
    "plt.ylabel(\"val\")\n",
    "#由图可知，Outcome分布不均衡，因为说明中自己未领会到哪两者相互之间影响，会造成何种影响，所以不设置权重\n",
    "#思考：接下来要做欠采样，过采样?"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 164,
   "metadata": {},
   "outputs": [],
   "source": [
    "#数据准备\n",
    "\n",
    "#分离输入特征和输出\n",
    "Y = DiabetesData[\"Outcome\"].values\n",
    "X = DiabetesData.drop(\"Outcome\",axis = 1)\n",
    "new_cols = X.columns\n",
    "#测试和训练数据分割\n",
    "from sklearn.model_selection import train_test_split\n",
    "X_train,X_test,Y_train,Y_test = train_test_split(X,Y,random_state = 22,test_size = 0.2)#题目要求"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 165,
   "metadata": {},
   "outputs": [],
   "source": [
    "#数据预处理\n",
    "\n",
    "#因为都要进行预处理，所以训练数据和测试数据不用分开，一起预处理\n",
    "from sklearn.preprocessing import StandardScaler\n",
    "#标准化器\n",
    "ss_X = StandardScaler()\n",
    "ss_Y = StandardScaler()\n",
    "#对二者标准化处理\n",
    "X_train = ss_X.fit_transform(X_train)\n",
    "X_test  = ss_X.transform(X_test)\n",
    "\n",
    "#Y_train = ss_Y.fit_transform(Y_train.reshape(-1,1)) \n",
    "#Y_test  = ss_Y.transform(Y_test.reshape(-1,1))\n",
    "\n",
    "#???经代码运行,若将Y_train，Y_test转换，在下面cell ,gcv.fit(X_train,Y_train)这行会出现值错误，经错误提示，做上方处理，即不做转换"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 166,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "log_loss_mean is:  0.4801558303073118\n"
     ]
    }
   ],
   "source": [
    "#Logistic 回归\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "from sklearn.cross_validation import cross_val_score\n",
    "#实例\n",
    "lr = LogisticRegression()\n",
    "\n",
    "loss = cross_val_score(lr,X_train,Y_train,cv = 4,scoring = \"neg_log_loss\")\n",
    "print ('log_loss_mean is: ',-loss.mean() )"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 167,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "GridSearchCV(cv=5, error_score='raise',\n",
       "       estimator=LogisticRegression(C=1.0, class_weight=None, dual=False, fit_intercept=True,\n",
       "          intercept_scaling=1, max_iter=100, multi_class='ovr', n_jobs=1,\n",
       "          penalty='l2', random_state=None, solver='liblinear', tol=0.0001,\n",
       "          verbose=0, warm_start=False),\n",
       "       fit_params=None, iid=True, n_jobs=1,\n",
       "       param_grid={'penalty': ['l1', 'l2'], 'C': [0.001, 0.01, 0.1, 1, 10, 100, 1000]},\n",
       "       pre_dispatch='2*n_jobs', refit=True, return_train_score='warn',\n",
       "       scoring='neg_log_loss', verbose=0)"
      ]
     },
     "execution_count": 167,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "#模型训练&模型选择&参数调优\n",
    "\n",
    "from sklearn.model_selection import GridSearchCV\n",
    "from sklearn.linear_model import LogisticRegression\n",
    "\n",
    "#参数准备\n",
    "#设置正则函数参数集合\n",
    "penaltys = [\"l1\",\"l2\"]\n",
    "#设置正则系数参数集合\n",
    "#C_sel = [0.001,0.01,0.1,0.15,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9,1,5,10,100,1000]\n",
    "C_sel = [0.001,0.01,0.1,1,10,100,1000]\n",
    "#合并转换成字典，因为\"网格搜索交叉验证\"参数原设计为字典类型\n",
    "adjust_parameters = dict(penalty = penaltys,C = C_sel )\n",
    "\n",
    "#分类器实例\n",
    "lr_sel = LogisticRegression()\n",
    "#构造GridSearchCV对象\n",
    "gcv = GridSearchCV(lr_sel,adjust_parameters,cv = 5, scoring = \"neg_log_loss\")\n",
    "#训练\n",
    "gcv.fit(X_train,Y_train)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 168,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Dell\\Documents\\anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('mean_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "C:\\Users\\Dell\\Documents\\anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('split0_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "C:\\Users\\Dell\\Documents\\anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('split1_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "C:\\Users\\Dell\\Documents\\anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('split2_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "C:\\Users\\Dell\\Documents\\anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('split3_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "C:\\Users\\Dell\\Documents\\anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('split4_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "C:\\Users\\Dell\\Documents\\anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('std_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n"
     ]
    },
    {
     "data": {
      "text/plain": [
       "{'mean_fit_time': array([0.00080767, 0.00100365, 0.0018065 , 0.00260549, 0.00160432,\n",
       "        0.00210552, 0.0013042 , 0.00090203, 0.00150123, 0.00340676,\n",
       "        0.00170684, 0.00070219, 0.00090218, 0.00080295]),\n",
       " 'mean_score_time': array([0.00099711, 0.00120196, 0.00300736, 0.00170493, 0.00110335,\n",
       "        0.00150404, 0.00090241, 0.00110312, 0.00090251, 0.001403  ,\n",
       "        0.0012013 , 0.00060163, 0.00040131, 0.00060115]),\n",
       " 'mean_test_score': array([-0.69314718, -0.64377099, -0.67925933, -0.52830817, -0.48380101,\n",
       "        -0.47930316, -0.47905382, -0.47943734, -0.48007185, -0.48013413,\n",
       "        -0.48020916, -0.48021674, -0.48022347, -0.48022515]),\n",
       " 'mean_train_score': array([-0.69314718, -0.64204571, -0.67900043, -0.5202757 , -0.46892374,\n",
       "        -0.4612408 , -0.45655103, -0.45641892, -0.45633242, -0.45633094,\n",
       "        -0.45633   , -0.45632998, -0.45632997, -0.45632997]),\n",
       " 'param_C': masked_array(data=[0.001, 0.001, 0.01, 0.01, 0.1, 0.1, 1, 1, 10, 10, 100,\n",
       "                    100, 1000, 1000],\n",
       "              mask=[False, False, False, False, False, False, False, False,\n",
       "                    False, False, False, False, False, False],\n",
       "        fill_value='?',\n",
       "             dtype=object),\n",
       " 'param_penalty': masked_array(data=['l1', 'l2', 'l1', 'l2', 'l1', 'l2', 'l1', 'l2', 'l1',\n",
       "                    'l2', 'l1', 'l2', 'l1', 'l2'],\n",
       "              mask=[False, False, False, False, False, False, False, False,\n",
       "                    False, False, False, False, False, False],\n",
       "        fill_value='?',\n",
       "             dtype=object),\n",
       " 'params': [{'C': 0.001, 'penalty': 'l1'},\n",
       "  {'C': 0.001, 'penalty': 'l2'},\n",
       "  {'C': 0.01, 'penalty': 'l1'},\n",
       "  {'C': 0.01, 'penalty': 'l2'},\n",
       "  {'C': 0.1, 'penalty': 'l1'},\n",
       "  {'C': 0.1, 'penalty': 'l2'},\n",
       "  {'C': 1, 'penalty': 'l1'},\n",
       "  {'C': 1, 'penalty': 'l2'},\n",
       "  {'C': 10, 'penalty': 'l1'},\n",
       "  {'C': 10, 'penalty': 'l2'},\n",
       "  {'C': 100, 'penalty': 'l1'},\n",
       "  {'C': 100, 'penalty': 'l2'},\n",
       "  {'C': 1000, 'penalty': 'l1'},\n",
       "  {'C': 1000, 'penalty': 'l2'}],\n",
       " 'rank_test_score': array([14, 12, 13, 11, 10,  2,  1,  3,  4,  5,  6,  7,  8,  9]),\n",
       " 'split0_test_score': array([-0.69314718, -0.64226185, -0.6812499 , -0.51852234, -0.4685792 ,\n",
       "        -0.455298  , -0.45077053, -0.44989718, -0.44987755, -0.44980211,\n",
       "        -0.44980873, -0.44980151, -0.44979956, -0.44980154]),\n",
       " 'split0_train_score': array([-0.69314718, -0.64286511, -0.6818522 , -0.52388302, -0.47434717,\n",
       "        -0.46722695, -0.46279383, -0.46267354, -0.46259248, -0.46259127,\n",
       "        -0.46259039, -0.46259037, -0.46259036, -0.46259036]),\n",
       " 'split1_test_score': array([-0.69314718, -0.64084983, -0.67703904, -0.51133396, -0.458961  ,\n",
       "        -0.43887877, -0.43006476, -0.42787528, -0.42702635, -0.42681232,\n",
       "        -0.42673116, -0.42670717, -0.42670328, -0.42669671]),\n",
       " 'split1_train_score': array([-0.69314718, -0.64389628, -0.67574419, -0.52778439, -0.48028135,\n",
       "        -0.47367588, -0.46975046, -0.46963932, -0.46957121, -0.46957006,\n",
       "        -0.46956933, -0.46956931, -0.46956931, -0.46956931]),\n",
       " 'split2_test_score': array([-0.69314718, -0.64675132, -0.67620111, -0.54046146, -0.50945033,\n",
       "        -0.50512405, -0.51158765, -0.51172078, -0.51340047, -0.51342062,\n",
       "        -0.51360807, -0.51360982, -0.51362538, -0.51362895]),\n",
       " 'split2_train_score': array([-0.69314718, -0.64050056, -0.67418232, -0.51533418, -0.46134438,\n",
       "        -0.45284126, -0.44760552, -0.44750115, -0.44740234, -0.44740129,\n",
       "        -0.4474002 , -0.44740019, -0.44740018, -0.44740018]),\n",
       " 'split3_test_score': array([-0.69314718, -0.64527151, -0.68164063, -0.53958537, -0.49149399,\n",
       "        -0.49776973, -0.4948197 , -0.49796363, -0.49823695, -0.49857238,\n",
       "        -0.4986093 , -0.49864476, -0.49864854, -0.49865212]),\n",
       " 'split3_train_score': array([-0.69314718, -0.64122239, -0.68259776, -0.51662762, -0.4655221 ,\n",
       "        -0.4576205 , -0.45309708, -0.45290202, -0.45281837, -0.45281638,\n",
       "        -0.45281548, -0.45281545, -0.45281545, -0.45281544]),\n",
       " 'split4_test_score': array([-0.69314718, -0.64374692, -0.68013104, -0.53180939, -0.49078758,\n",
       "        -0.4998664 , -0.50852268, -0.51024809, -0.51234764, -0.51259537,\n",
       "        -0.51282187, -0.51285406, -0.51287432, -0.51288019]),\n",
       " 'split4_train_score': array([-0.69314718, -0.64174422, -0.68062565, -0.51774932, -0.46312369,\n",
       "        -0.45483942, -0.44950824, -0.44937858, -0.44927769, -0.44927571,\n",
       "        -0.44927461, -0.44927458, -0.44927457, -0.44927457]),\n",
       " 'std_fit_time': array([2.50051042e-04, 7.00804637e-07, 9.84925786e-04, 2.33837886e-03,\n",
       "        4.91342041e-04, 4.91382818e-04, 2.44739541e-04, 3.74763387e-04,\n",
       "        6.29819916e-04, 1.65678198e-03, 1.17159778e-03, 2.45243122e-04,\n",
       "        2.00391404e-04, 7.51949088e-04]),\n",
       " 'std_score_time': array([0.00030768, 0.00040217, 0.00353345, 0.00117105, 0.00020077,\n",
       "        0.00031719, 0.00020218, 0.00073653, 0.0005848 , 0.00037554,\n",
       "        0.00039916, 0.00020022, 0.0003752 , 0.00049084]),\n",
       " 'std_test_score': array([0.        , 0.00209324, 0.00222073, 0.01157886, 0.01796116,\n",
       "        0.02697518, 0.03277343, 0.0342367 , 0.03522001, 0.03538112,\n",
       "        0.03548478, 0.03550313, 0.03551166, 0.0355154 ]),\n",
       " 'std_train_score': array([0.        , 0.00120435, 0.00339211, 0.00476451, 0.00722589,\n",
       "        0.00793853, 0.00842319, 0.00843043, 0.00844178, 0.00844195,\n",
       "        0.00844209, 0.00844209, 0.00844209, 0.00844209])}"
      ]
     },
     "execution_count": 168,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "gcv.cv_results_"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 169,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "0.479053824273715\n",
      "{'C': 1, 'penalty': 'l1'}\n"
     ]
    }
   ],
   "source": [
    "print(-gcv.best_score_) \n",
    "print(gcv.best_params_)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 170,
   "metadata": {},
   "outputs": [
    {
     "name": "stderr",
     "output_type": "stream",
     "text": [
      "C:\\Users\\Dell\\Documents\\anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('mean_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n",
      "C:\\Users\\Dell\\Documents\\anaconda\\lib\\site-packages\\sklearn\\utils\\deprecation.py:122: FutureWarning: You are accessing a training score ('std_train_score'), which will not be available by default any more in 0.21. If you need training scores, please set return_train_score=True\n",
      "  warnings.warn(*warn_args, **warn_kwargs)\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d69b924860>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#可视化                      虽然题目未做要求，但还是做了比较直观\n",
    "test_mean = gcv.cv_results_['mean_test_score']\n",
    "train_mean = gcv.cv_results_['mean_train_score']\n",
    "test_std   = gcv.cv_results_['std_test_score']\n",
    "train_std  = gcv.cv_results_['std_train_score']\n",
    "\n",
    "n_C = len(C_sel)    \n",
    "n_penaltys = len(penaltys)\n",
    "\n",
    "test_scores = np.array(test_mean).reshape(n_C,n_penaltys)\n",
    "train_scores = np.array(train_mean).reshape(n_C,n_penaltys)\n",
    "test_stds = np.array(test_std).reshape(n_C,n_penaltys)\n",
    "train_stds = np.array(train_std).reshape(n_C,n_penaltys)\n",
    "\n",
    "x_dir = np.log10(C_sel)\n",
    "for i,value in enumerate(penaltys):\n",
    "#     print(i)\n",
    "#     print(str(value))\n",
    "    plt.errorbar(x_dir, test_scores[:,i], yerr=test_stds[:,i] ,label = (penaltys[i] + str(value)))\n",
    "    plt.errorbar(x_dir, train_scores[:,i], yerr=train_stds[:,i] ,label =( penaltys[i]+ str(value)))#图中线的标识框没转换过来\n",
    "plt.legend(\"best\")\n",
    "plt.xlabel(\"log(C)\")\n",
    "plt.ylabel(\"neg_log_loss\")\n",
    "plt.savefig('LogisticGridSearchCV_C.png')\n",
    "\n",
    "plt.show()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 180,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "acc: 0.7342657342657343\n",
      "acc: 0.7272727272727273\n",
      "acc: 0.7272727272727273\n",
      "acc: 0.7342657342657343\n",
      "acc: 0.7342657342657343\n",
      "acc: 0.7552447552447552\n",
      "acc: 0.6923076923076923\n",
      "max_acc is 0.7552447552447552 \n",
      "adjust_C is 100.0\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d69bdf2b00>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#线性 SVM\n",
    "\n",
    "# #要和logistic回归比较，所以采用交叉验证，GridSearchCV,fit，且评价指标一致\n",
    "# from sklearn.cross_validation import cross_val_score\n",
    "# loss = cross_val_score(lr, X_train, Y_train, cv=5, scoring='neg_log_loss')        \n",
    "\n",
    "# print(\"cv loss_mean is %s\"% -loss.mean())\n",
    "\n",
    "# from sklearn.model_selection import GridSearchCV\n",
    "# from sklearn.svm import LinearSVC\n",
    "\n",
    "# LnSvmPenaltys = ['l1','l2']\n",
    "# LnSvmC = [0.001, 0.01, 0.1, 1, 10, 100, 1000]\n",
    "# adjust_parameters = dict(penalty = LnSvmPenaltys,C = LnSvmC )\n",
    "\n",
    "# LnSvmSVC = LinearSVC().fit(X_train, Y_train)\n",
    "# gcv= GridSearchCV(LnSvmSVC, adjust_parameters,cv=5, scoring='neg_log_loss')#这个步骤好像不太合适\n",
    "\n",
    "# y_predict = LnSvmSVC.predict(X_test)\n",
    "# print(\"Classification report for classifier %s:\\n%s\\n\"  % (LnSvmSVC, metrics.classification_report(Y_test, y_predict)))\n",
    "# print(\"Confusion matrix:\\n%s\" % metrics.confusion_matrix(Y_test, y_predict))\n",
    "\n",
    "def fit_grid_Linear(C, X_train, Y_train, X_test,Y_test):\n",
    "    LnSvmSVC =  LinearSVC( C = C)\n",
    "    LnSvmSVC = LnSvmSVC.fit(X_train, Y_train)\n",
    "    \n",
    "    acc = LnSvmSVC.score(X_test, Y_test)\n",
    "    \n",
    "    print(\"acc: {}\".format(acc))\n",
    "    return acc\n",
    "\n",
    "LnSvmC = np.logspace(-3, 3, 7)\n",
    "\n",
    "acc_s = []\n",
    "for i, LnSvm_C in enumerate(LnSvmC):\n",
    "    temp = fit_grid_Linear(LnSvm_C, X_train, Y_train, X_test, Y_test)\n",
    "    acc_s.append(temp)\n",
    "    if temp >= acc_s[0]:\n",
    "        max_acc   = temp\n",
    "        adjust_C  = LnSvm_C\n",
    "\n",
    "print(\"max_acc is %s \\nadjust_C is %s\" % (max_acc,adjust_C))\n",
    "x_dir = np.log10(LnSvmC)\n",
    "\n",
    "pyplot.plot(x_dir, np.array(acc_s), 'b-')\n",
    "    \n",
    "pyplot.legend(\"best\")\n",
    "pyplot.xlabel( 'log(C)' )                                                                                                      \n",
    "pyplot.ylabel( 'acc' )\n",
    "pyplot.savefig('LnSvmDiebetes.png' )\n",
    "\n",
    "pyplot.show()\n",
    "\n",
    "#比较  ：logistic回归和线性SVM\n",
    "#相同点：C的宽度一样\n",
    "#陈述：    主要原因是自己不能实现固定logistic回归和线性SVM的这个变量的前提下，将其他等因素划过划归在同一环境下，所以自身不能从客观的角度\n",
    "#      评价性能优良。"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 139,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "<-------------------------------------------------------------->\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.7622377622377622\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6853146853146853\n",
      "acc 0.7622377622377622\n",
      "acc 0.7762237762237763\n",
      "acc 0.6993006993006993\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.7622377622377622\n",
      "acc 0.7552447552447552\n",
      "acc 0.7762237762237763\n",
      "acc 0.6643356643356644\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.7342657342657343\n",
      "acc 0.7482517482517482\n",
      "acc 0.7342657342657343\n",
      "acc 0.6643356643356644\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.7552447552447552\n",
      "acc 0.7552447552447552\n",
      "acc 0.6363636363636364\n",
      "acc 0.6643356643356644\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "acc 0.6923076923076923\n",
      "<-------------------------------------------------------------->\n"
     ]
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<matplotlib.figure.Figure at 0x1d69bf49198>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "#RBF 核的 SVM  \n",
    "from sklearn.svm import SVC\n",
    "\n",
    "def fit_grid_RBF(C,gamma,X_train,Y_train,X_val,Y_val):\n",
    "    SVC_RBF = SVC(C = C,kernel = \"rbf\",gamma = gamma)#实例\n",
    "    SVC_RBF = SVC_RBF.fit(X_train,Y_train)#训练\n",
    "    acc = SVC_RBF.score(X_val,Y_val)#返回得分\n",
    "    print(\"acc {}\".format(acc))\n",
    "    return acc\n",
    "\n",
    "print(\"<-------------------------------------------------------------->\")\n",
    "RBF_C_sel     = np.logspace(-3,3,7)#正则系数\n",
    "RBF_gamma_sel = np.logspace(-3,3,7)#核函数宽度\n",
    "\n",
    "acc_sum = []\n",
    "\n",
    "for i,singleC in enumerate(RBF_C_sel):\n",
    "    for j,gamma in enumerate(RBF_gamma_sel):\n",
    "        temp = fit_grid_RBF(singleC,gamma,X_train,Y_train,X_test,Y_test)\n",
    "        acc_sum.append(temp)\n",
    "print(\"<-------------------------------------------------------------->\")\n",
    "\n",
    "acc_sumfin = np.array(acc_sum).reshape(len(RBF_C_sel),len(RBF_gamma_sel))\n",
    "x_dir = np.log10(RBF_C_sel)\n",
    "for iter,gamma in enumerate(RBF_gamma_sel):\n",
    "    plt.plot(x_dir,np.array(acc_sumfin[:,iter]),label = ' Test - log(gamma)' + str(np.log10(gamma)))#图中线的标识框没转换过来\n",
    "    \n",
    "plt.legend(\"best\")\n",
    "plt.xlabel(\"logC\")\n",
    "plt.ylabel(\"acc\")\n",
    "plt.savefig(\"RBF_SVW_diebetes.png\")\n",
    "plt.show()"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
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